7.3 SPSS Activity: Calculating and Interpreting Results for a Two-Way Between-Subjects Factorial ANOVA (2x2 design).

Activity 7.3 Instructions Document

Name: 7.3 SPSS Activity: Calculating and Interpreting Results for a Two-Way Between-Subjects

Factorial ANOVA (2x2 design).

The following activity will present an opportunity to put into practice what you have learned and read

about regarding Two-Way Between-Subjects Factorial ANOVA. The narratives supplied in these

exercises will provide all the information you will need to determine what main effects and interactions

are to be analyzed. Please read the following narrative and then use the Excel spreadsheet provided to

import the data into SPSS to construct a dataset that SPSS can use to perform the proper calculations and

post hoc analyses.

Problem Narrative 7.3:

A researcher at the FAA wants to test the effects of age and experience on pilot performance. To do this,

the researcher plans to use a Flight Training Device to run participants through a simulation that will

collect data on altitude, heading, and speed while executing a series of flight maneuvers through a number

of pre-programmed way-points. The two variables will be age (young and older) and experience (pilot

and non-pilot). To test the effects of age and experience, the researcher decided to use four groups, young

pilots, older pilots, young non-pilots, and older non-pilots. The information from the data to be collected

(altitude, heading, and speed) will be recorded and numerically combined to obtain a single numerical

value called "pilot skills performance".

To analyze the data, a two-way between-subjects factorial ANOVA will be used to analyze the main

effects of age and experience on pilot skills performance. Young was defined as under 40 years old, and

older was defined as 40 or older. The interaction of age and experience will also be analyzed for pilot

skills performance. Based on existing literature in this area, the researcher has determined that 10

participants per group should provide enough power given a large effect size and an alpha level of p <

0.05.

The pilot skills performance scores range from 0 - 100 with larger scores indicating better performance.

The hypothesis is that older pilots will perform better than younger pilots and that there will be an

interaction between age and experience.

Download the Excel spreadsheet “7.3 Data Input” and import the spreadsheet into SPSS for subsequent

analyses

Part I: Import Data into SPSS:

Use the spreadsheet you just downloaded “7.3 Data Input” and import the data in this spreadsheet into

SPSS for subsequent analyses. Name your SPSS data file “7.3 SPSS Pilot Performance Dataset” with

the “.sav” extension. Your SPSS data file should be ready to use for analysis.

Part II: Short Answer Questions:

Create an MSWord document to answer the short answer questions from part II and III of this exercise.

The name of the file will be “7.3 SPSS Exercise – Short Answer Questions”. Save this for subsequent

upload as one of your deliverables for this exercise.

Answer the following based on the narrative and data provided:

1. What are the dependent and independent variables in this scenario? Name/List them.

2. How many levels of each independent variable are there? Name/list them?

3. What interaction can be examined and what post hoc test will you use to examine the interactions

for significance?

4. What is the hypothesis?

5. What does it mean if you have a significant interaction between the variables being examined?

6. What does it mean if you do not find any significant interactions between the variables being

examined?

Part III: Running the Appropriate Analysis in SPSS:

Using the “7.3 SPSS Pilot Performance Dataset” you created previously in this exercise, run the

appropriate ANOVA (F test) in SPSS. When running an ANOVA on this type of design in SPSS, you

should use a General Linear Model – Univariate, with Pilot Skills Performance as the dependent variable

and Age and Experience as the Fixed Factors. Under “plots”, make sure you select all possible plots (Age,

Experience, Age*Experience, and Experience*Age). Post hocs cannot be performed on this design

because each independent variable has only 2 levels of variable. Under “options”, make sure you display

means for Overall, Age, Experience, and Age*Experience, compare main effects, and check off the boxes

for Descriptive Stats, Estimates of Effect Size, and Observed Power.

Add the following to your list of short answer questions as information obtained from your SPSS output

file.

7. What are your numerical results? Make sure to report your results in proper APA format (i.e.

F(dfBG, dfE) = Fcalc, p= x.xx).

8. Did you find any significant results (main effects or interactions?)

Save the GLM ANOVA output as “7.3 SPSS Pilot Performance Output” as an “.spv” file to upload as a

deliverable at the conclusion of this exercise.

Part IV: Results Write Up:

Write up the results of your data analysis in standard APA format being sure to mention all relevant

variables and findings in your write up. Make sure your format adheres to APA format and guidelines.

Save the document as “7.3 SPSS Results Write Up”.

(If you have questions about what a complete results write up for an ANOVA looks like, either look up

conference and journal articles that use t-tests as their statistical analysis, or contact your instructor for

specific guidance.)

Your deliverables for this SPSS exercise will be:

1. The IBM SPSS data file “7.3 SPSS Pilot Performance Dataset”.

2. The IBM SPSS viewer file “7.3 SPSS Pilot Performance Output”.

3. The Short Answer document “7.3 SPSS Exercise – Short Answer Questions”.

4. The APA formatted results write up “7.3 SPSS Results Write Up”.

Upload all four of these files as your submission for this exercise to be considered for full credit.